Feminist Praxis Revisited: Critical Reflections on University–Community Engagement edited by A. Dean, J. L. Johnson, & S. Luhmann
Bibliographic record
Abstract
In Feminist Praxis Revisited, a new edited collection from Amber Dean, Jennifer L. Johnson, and Susanne Luhmann, the contributors offer insightful critiques of service-learning (SL) and community engagement within the field of women’s and gender studies (WGS) in Canada. Drawing from Freire (1970), the authors operationalize praxis as putting theories/ideas into action, especially through SL and community engagement. The contributors adeptly problematize several core assumptions of SL by asking questions such as: What does it mean to “learn elsewhere,” and why do educators think it is necessary? And how can WGS promote activism within the neoliberal university context, where community service and job preparation are emphasized? Although all the chapters are set in the Canadian context, readers from any developed nation likely will resonate with the struggles outlined in the book. However, the authors sometimes raise more questions than they answer, offering few practical suggestions for the audience. Nevertheless, Feminist Praxis Revisited is a useful resource for critical educators who want to re-evaluate their classroom and community praxis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.026 | 0.033 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.009 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".